Efficient vehicle driving on multi-lane roads using model predictive control under a connected vehicle environment

Anticipative control of vehicles is a potential approach for improving travel efficiency of individual vehicles, smoothing traffic flows on urban roads, alleviating impacts on the environment and elevating comforts of the users in various respects. This paper presents such a vehicle driving system in a model predictive control (MPC) framework to efficiently drive a vehicle on multi-lane roads. Anticipation enhances the driving intelligence and strengthens the vehicle's ability in taking advance action, e.g., lane change, speed adjustment, in a dynamically varying traffic environment. More elaborately, presuming a connected vehicle environment, the system receives the information form the surrounding vehicles and infrastructure instantly through V2X communication systems and, using dynamical models, predicts the future road-traffic states. Considering relevant constraints and a performance index, the system generates the optimal acceleration and executes lane change maneuver optimally if long term advantages are anticipated. Numerical simulation in realistic traffic flow conditions reveals that the vehicles with the proposed driving system improve their travel efficiency significantly.